Cooperative Studies Program Epidemiology Center-Durham, Durham VA Health Care System, Durham, NC, USA.
Department of Radiation Oncology, University of California, San Francisco, San Francisco, CA, USA.
Sci Rep. 2021 Apr 14;11(1):8104. doi: 10.1038/s41598-021-85546-2.
Understanding patient accumulation of comorbidities can facilitate healthcare strategy and personalized preventative care. We applied a directed network graph to electronic health record (EHR) data and characterized comorbidities in a cohort of healthy veterans undergoing screening colonoscopy. The Veterans Affairs Cooperative Studies Program #380 was a prospective longitudinal study of screening and surveillance colonoscopy. We identified initial instances of three-digit ICD-9 diagnoses for participants with at least 5 years of linked EHR history (October 1999 to December 2015). For diagnoses affecting at least 10% of patients, we calculated pairwise chronological relative risk (RR). iGraph was used to produce directed graphs of comorbidities with RR > 1, as well as summary statistics, key diseases, and communities. A directed graph based on 2210 patients visualized longitudinal development of comorbidities. Top hub (preceding) diseases included ischemic heart disease, inflammatory and toxic neuropathy, and diabetes. Top authority (subsequent) diagnoses were acute kidney failure and hypertensive chronic kidney failure. Four communities of correlated comorbidities were identified. Close analysis of top hub and authority diagnoses demonstrated known relationships, correlated sequelae, and novel hypotheses. Directed network graphs portray chronologic comorbidity relationships. We identified relationships between comorbid diagnoses in this aging veteran cohort. This may direct healthcare prioritization and personalized care.
了解患者合并症的积累可以促进医疗保健策略和个性化预防保健。我们将有向网络图应用于电子健康记录 (EHR) 数据，并对接受筛查结肠镜检查的健康退伍军人队列中的合并症进行了特征描述。退伍军人事务合作研究计划 #380 是一项前瞻性纵向研究，用于筛查和监测结肠镜检查。我们确定了至少有 5 年相关 EHR 病史（1999 年 10 月至 2015 年 12 月）的参与者最初出现三位数 ICD-9 诊断的情况。对于影响至少 10%患者的诊断，我们计算了成对的时间顺序相对风险 (RR)。iGraph 用于生成 RR>1 的合并症有向图以及汇总统计信息、关键疾病和社区。基于 2210 名患者的有向图可视化了合并症的纵向发展。顶级枢纽（前序）疾病包括缺血性心脏病、炎症和中毒性神经病以及糖尿病。顶级权威（后续）诊断为急性肾衰竭和高血压性慢性肾衰竭。确定了四个相关合并症社区。对顶级枢纽和权威诊断的仔细分析表明存在已知关系、相关后果和新假设。有向网络图描绘了时间顺序的合并症关系。我们在这个老龄化的退伍军人队列中发现了合并症诊断之间的关系。这可能会指导医疗保健的优先级和个性化护理。
